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Technical Studies Reference

Inverse Fisher Transform with RSI

The study calculates and displays an Inverse Fisher Transform of an RSI.

Let \(C\) be a random variable denoting the Close Price, and let the RSI Length and RSI MovAvg Length Inputs be denoted as \(n_{RSI}\) and \(n_{\overline{RSI}}\), respectively. The Moving Average used in computing \(RSI_t(C,n_{RSI})\) is determined by the RSI Internal MovAvg Type Input. We subject the RSI to the following transformation.

\(RSI^*_t(C,n_{RSI}) = \frac{1}{10}\left(RSI_t(C,n_{RSI}) - 50\right)\)

We denote the Weighted Moving Average of \(RSI^*_t(C,n_{RSI})\) as \(\overline{RSI^*}_t(C,n_{RSI},n_{\overline{RSI}})\), and we compute it as follows.

\(\overline{RSI^*}_t(C,n_{RSI},n_{\overline{RSI}}) = WMA_t\left(RSI^*(C,n_{RSI}), n_{\overline{RSI}}\right)\)

The Inverse Fisher Transform with RSI is at Index \(t\) is then given by \(IFT_t\left(\overline{RSI^*}(C,n_{RSI},n_{\overline{RSI}})\right)\). The explicit formula is given below. It is calculated for \(t \geq n_{RSI} + n_{\overline{RSI}}\).

\(\displaystyle{IFT_t\left(\overline{RSI^*}(C,n_{RSI},n_{\overline{RSI}})\right) = \frac{\exp\left(2\overline{RSI^*}(C,n_{RSI},n_{\overline{RSI}})\right) - 1}{\exp\left(2\overline{RSI^*}(C,n_{RSI},n_{\overline{RSI}})\right) + 1}}\)

Let the Line Value Input be denoted as \(l\). In addition to the graph of \(IFT_t\left(\overline{RSI^*}(C,n_{RSI},n_{\overline{RSI}})\right)\), this study displays horizontal lines at levels \(\pm l\).



The spreadsheet below contains the formulas for this study in Spreadsheet format. Save this Spreadsheet to the Data Files Folder.

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*Last modified Thursday, 26th July, 2018.